6 papers
Compositional Cross-Modality Translation via Whole-Volume Multitask Latent Flow Matching
Daniele Molino, Alessio Zoboli, Camillo Maria Caruso +2
Cross-modality medical image translation can reduce the burden of multi-modal acquisitions, yet the field remains constrained by two coupled limitations: methods operate on 2D slic…
Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariates
Irene Iele, Giulia Romoli, Daniele Molino +4
Short-term forecasting of vegetation dynamics is a key enabler for data-driven decision support in precision agriculture. Normalized Difference Vegetation Index (NDVI) forecasting…
Retrieval-Augmented Anatomical Guidance for Text-to-CT Generation
Daniele Molino, Camillo Maria Caruso, Paolo Soda +1
Text-conditioned generative models for volumetric medical imaging provide semantic control but lack explicit anatomical guidance, often resulting in outputs that are spatially ambi…
From Alignment to Synthesis Contrastive Volumetric Grounding for Text-to-CT Generation
Daniele Molino, Camillo Maria Caruso, Filippo Ruffini +2
Generating semantically controllable 3D CT volumes from radiology reports requires more than a rich text encoder, it requires vision-language alignment grounded in volumetric space…
XGeM: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation
Daniele Molino, Francesco Di Feola, Eliodoro Faiella +5
The adoption of Artificial Intelligence in medical imaging holds great promise, yet it remains hindered by challenges such as data scarcity, privacy concerns, and the need for robu…
Any-to-Any Vision-Language Model for Multimodal X-ray Imaging and Radiological Report Generation
Daniele Molino, Francesco di Feola, Linlin Shen +2
Generative models have revolutionized Artificial Intelligence (AI), particularly in multimodal applications. However, adapting these models to the medical domain poses unique chall…